Medium-range structure of vitreous SiO2

Using a density-functional framework, we investigate the vibrational spectra of vitreous SiO2 to determine to what extent these spectra provide information about the medium-range structure of the oxide network. We carry out a comparative study involving three model structures, which all feature a nondefective network of corner-sharing tetrahedra but differ through their Si-O-Si bond-angle distributions and ring statistics. We first address the results of typical diffraction probes. Fair agreement with experiment is achieved for the total neutron and total x-ray structure factors of all models, indicating limited sensitivity of these structure factors to the medium-range structure. The same consideration also applies to the Si-O and O-O partial structure factors. At variance, the Si-Si partial structure factor is found to be highly sensitive to the Si-O-Si bond-angle distribution. We then address typical vibrational spectra, such as the inelastic neutron spectrum, the infrared spectra, and the Raman spectra. Our study indicates that the considered experimental data are globally consistent with a medium-range structure characterized by an average Si-O-Si bond angle of 148° and with small-ring concentrations as derived from the intensities of the experimental Raman defect lines. To describe the infrared and Raman couplings, our work also introduces parametric models which reproduce well the spectra calculated from first principles.

Identifier
Source https://archive.materialscloud.org/record/2019.0086/v1
Metadata Access https://archive.materialscloud.org/xml?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:276
Provenance
Creator Giacomazzi, Luigi; Umari, Paolo; Pasquarello, Alfredo
Publisher Materials Cloud
Publication Year 2019
Rights info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Contact archive(at)materialscloud.org
Representation
Language English
Resource Type Dataset
Discipline Materials Science and Engineering